Abstract: The present disclosure relates to a method for a weighting graph comprising nodes representing entities and edges representing relationships between entities in accordance with one or more domains. The method comprises: pre-processing the graph comprising assigning weights to the nodes and/or the edges of the graph in accordance with a specific domain of the domains, wherein the weight indicates a domain specific data quality problem of attribute values representing an edge of the edges and/or an entity involved in that edge. The weighted graph may be provided for enabling a processing of the graph in accordance with the specific domain.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: Lifecycle management for blueprints of information technology systems includes determining, using a processor, a component referenced by a blueprint defining an information technology system and determining a component tool used to manage the component. The component is registered with a sensor within the component tool. Responsive to detecting a change in status of the component within the component tool, the sensor sends a notification.

Abstract: Lifecycle management for blueprints of information technology systems includes determining, using a processor, a component referenced by a blueprint defining an information technology system and determining a component tool used to manage the component. The component is registered with a sensor within the component tool. Responsive to detecting a change in status of the component within the component tool, the sensor sends a notification.

Abstract: The present disclosure relates to a method for data anonymization of a database system. The method comprises: determining if a first dataset and second dataset of the database system have a relationship indicative of an entity having values in the two datasets. A request may be received from a user for at least one of the first and second datasets. In case the first dataset and second dataset have the relationship, at least one of the first and second datasets may be modified such that the indication of the entity is not accessible to the user. And the requested dataset may be provided.

Abstract: Securely matching encrypted entities by receiving data, segmenting the data into a plurality of categories, selecting encryption key(s) according to a data category of the plurality of data categories, encrypting the data of the data category using the encryption key(s), and comparing the encrypted data to previously encrypted data of the data category.

Abstract: A computer-implemented method includes generating, by a computer device, a plurality of clusters of unmanned aerial vehicles (UAVs) from a plurality of UAVs having different UAV characteristics, the clusters being generated based on the UAV characteristics of each of the UAVs; determining, by the computer device, task characteristics for a first task; selecting, by the computer device, one of the clusters based on the task characteristics of the first task; assigning to the first task, by the computer device, a first UAV of the plurality of UAVs from the selected cluster; receiving, by the computer device, task feedback regarding an attempt by the first UAV to complete the first task; and reassigning, by the computer device, and based on the task feedback, the first UAV to a determined one of the plurality of clusters.

Abstract: A method for presenting search query results is provided. The method may include detecting an occurrence of the trigger event. The method may include determining a category of information based on data associated with the trigger event. The method may include identifying at least one constraint based on the determined category of information. The method may include appending to the identified at least one constraint to the determined category of information. The method may include generating at least one search query. The method may include selecting at least one candidate website based on the category of information. The method may include performing the at least one search query on the at least one candidate website. The method may include filtering each search query result within the search query results. The method may include sending each filtered search query result within the search query results to a user.

Abstract: Embodiments of the present invention disclose generating a data profiling jobs for source data in a data processing system, the source data being described by at least one source functional data model. A target functional data model is provided, for describing target data that can be generated from the source data. One or more source functional data models are identified that correspond to the target functional data model. At least one functional source-to-target model mapping is associated to at least one source-target pair based on the target functional data model and identified source functional data models. A physical source-to-target model mapping for at least one source-target pair based on the logical source-to-target model mapping is calculated. For all physical source attributes, the needed data profiling jobs are generated based on the target attribute for analyzing the physical source attributes.

Abstract: A processor receives statistical information about a data set included in a column of a data table. The processor receives additional information about the data set that indicates a data format utilized by the data set and a type of information represented by the data set. The processor generates a data dictionary for compression of the data set based, at least in part, on the statistical information and the additional information. The data dictionary is created such that the data dictionary is capable of compressing data that is statistically predicted to be received at a future point.

Abstract: Embodiments of the present invention disclose generating a data profiling jobs for source data in a data processing system, the source data being described by at least one source functional data model. A target functional data model is provided, for describing target data that can be generated from the source data. One or more source functional data models are identified that correspond to the target functional data model. At least one functional source-to-target model mapping is associated to at least one source-target pair based on the target functional data model and identified source functional data models. A physical source-to-target model mapping for at least one source-target pair based on the logical source-to-target model mapping is calculated. For all physical source attributes, the needed data profiling jobs are generated based on the target attribute for analyzing the physical source attributes.

Abstract: Embodiments of the present invention describe creating a mesh network of autonomous vehicles. Embodiments describe, for a set of autonomous vehicles configured to perform joint tasks, creating a plurality of subset networks of autonomous vehicles based on geographical proximity, wherein the plurality of subset networks of autonomous vehicles overlap to form a mesh network of autonomous vehicles, and wherein the mesh network of autonomous vehicles and the subset networks of autonomous vehicles support a non-centralized task assignment feature to assign tasks to autonomous vehicles in the mesh network. Additionally, embodiments describe sending a status signal to a first autonomous vehicle in the mesh network via a second autonomous vehicle in the mesh network, wherein the first autonomous vehicle is in a same subset network of autonomous vehicles as the second autonomous vehicle.

Abstract: A method for relating different types of records. The method may include providing comparison functions, wherein each comparison function corresponds to a semantical class, and wherein a computational cost is associated with each comparison function. The method may include determining one or more attribute pairs between the different types of records. The method may include sorting the comparison functions according to a determined accuracy. The method may include selecting a set of comparison functions associated with semantical classes according to a predefined rule. The method may include determining a total computational cost based on the computational cost of the selected set of comparison functions. The method may include determining whether two or more records are related using the selected set of comparison functions. The method may include relating the two or more records. The method may include determining a rate of false negative records.

Abstract: A logging process in a data storage system having a set of storage tiers, each storage tier of the set of storage tiers having different performance characteristics, wherein the set of storage tiers is divided into a plurality of subsets of storage tiers using the performance characteristics, may include initiating the logging process for creating a separate log file for each of the plurality of subsets of storage tiers for maintaining a history of data changes in the subset of storage tiers, thereby creating a plurality of log files. In response to a change in data stored in at least one storage tier of a subset of storage tiers of the plurality of subsets of storage tiers, one or more log records including information about the change may be generated and written into respective log files.

Abstract: A method, system, and computer program product for identifying reference data values in a source data set. The method may include inputting a block of attribute values to a predefined machine learning model. The method may also include receiving an indication of a presentation layout of the block of the attribute values and an associated reference data extraction method. The method may also include determining a reading direction of the block of values. The method may also include identifying one or more inspection areas in the reading direction of the block of values. The method may also include determining sets of the one or more inspection areas that share a common presentation feature. The method may also include identifying tokens in an inspection area. The method may also include determining if the inspection area includes reference data values. The method may also include outputting the reference data values.

Abstract: A computer-implemented method includes determining, by a computer device, composite view rules for combining first data from a first data record and second data from a second data record to create a composite view of an entity in a master data management system; receiving, by the computer device, the first data; receiving, by the computer device, the second data; creating, by the computer device, the composite view from the first data and the second data based on the composite view rules; physically materializing the composite view on a storage device; preserving, by the computer device, the first data record; and preserving, by the computer device, the second data record.

Abstract: A method, a computer system, and a computer program product for adaptive learning is provided. Embodiments of the present invention may include combining a plurality of users of an adaptive learning platform into one or more clusters based on an initial questionnaire. Embodiments of the present invention may include monitoring key events of the plurality of users, wherein the key events are indicative of a level of comprehension of a topic for the plurality of users. Embodiments of the present invention may include adjusting the combination of the plurality of users in the one or more clusters based on the key events. Embodiments of the present invention may include adjusting the initial questionnaire.

Abstract: A method is disclosed for a database system that includes a set of data blocks comprising records having attributes. The set of data blocks are instances of at least one block type. The block type is defined by a subset of one or more attributes of the attributes. An instance of the block type comprises records having one distinct group of values of the subset of attributes. The method includes detecting that a subset of one or more data blocks of the block type, of the set of data blocks, reached a first maximum number of records. The method includes determining an additional attribute of the attributes to define a new block type by the combination of the additional attribute and the subset of attributes that define the block type. The method includes creating one or more data blocks which are instances of the new block type.

Abstract: A method includes training a machine learning model using a current set of labeled data points. Each of the data points is multiple data records. A label of a data point indicates a classification of the data point. The training results in a trained machine learning model configured to classify a data point as representing a same entity or different entities. The method includes selecting a subset of unlabeled data points from a current set of unlabeled data points using classification results of the current set of unlabeled data points. The method includes providing the subset of unlabeled data points to a classifier and in response to providing receiving labels of the subset of unlabeled data points. The method may be repeated using the subset of labeled data points in addition to the current set of labeled data points as the current set of labeled data points.

Abstract: A system and method are provided for predicting a signal strength for a specific location. The method includes operations for predicting mobile device signal strength by building a database of mobile signal information. The mobile signal information includes signal strength for a plurality of mobile devices located at a plurality of three-dimensional, geospatial coordinates and utilizing a plurality of mobile signal providers/carriers. The method predicts, using the database, a signal strength for a particular mobile device at a particular set of three-dimensional, geospatial coordinates utilizing a particular mobile signal provider/carrier and displays the prediction at a specific time.